GigaMedia Ltd

GigaMedia Ltd(GIGM)價格預測

$1.370

-0.029 (-2.14%)收盤時

價格預測

1-Day Price Prediction
+0.93%
1-Week Prediction
+1.14%
1-Month Prediction
—
2026 Prediction
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2030 Prediction
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在 App 中開啟以解鎖更長週期的預測。

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GIGM 相似圖表分析預測

Alphio's GIGM stock price prediction model matches the current GigaMedia Ltd tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $1.38 (+0.93%). The 1-week path is $1.39 (+1.14%). Longer windows use the same pattern set plus seasonality; the 1-month and multi-year forecasts sit behind unlock because they include precise min / avg / max bands.

該買進 GigaMedia Ltd 股票嗎?

GigaMedia Ltd is a good buy right now due to its promising financial turnaround, as evidenced by a significant increase in gross margin to 63.21% in Q3 2026 and a forward P/E ratio of 5.29, suggesting it is undervalued compared to its earnings potential. The main risk is its recent performance, with a YTD change of -11.04%, indicating volatility.

GIGM 股價於 Friday 收在 $1.37,此前下跌 -2.14%

GigaMedia Ltd (GIGM) last closed at $1.37, losing -2.14%. These facts feed the 1-day and 1-week GIGM price prediction above.

預測驅動因素

GigaMedia Ltd(GIGM)的預測驅動因素綜合了相似的圖表形態、季節性與移動平均線。

Similar patterns

Positive

Bullish

Seasonality

Positive

Bullish

SMA 20

Positive

Bullish

SMA 200

Negative

Bearish

相似圖表形態

近期走勢與 GIGM 最接近的股票,依相似度排序。

GIGM 季節性分析

Historically the probability of a positive November return for GIGM is 86.36%. November offers the highest probability of a positive month at 86.36%, while July is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.

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GIGM 十年價格預測

月份最低價平均價最高價潛在報酬率
Nov 2026$1.17$1.36$1.64-0.83%
Dec 2026$1.58$1.61$1.75+17.85%

2026 年,GigaMedia Ltd(GIGM)預計區間為 $1.17 至 $1.75。

GigaMedia Ltd 2026 年月度預測

GIGM 2026 年 Nov 預測
潛在報酬率:-0.83%

2026 年 Nov,GigaMedia Ltd 預計均價 $1.36,最低 $1.17,最高 $1.64。

GIGM 2026 年 Dec 預測
潛在報酬率:17.85%

2026 年 Dec,GigaMedia Ltd 預計均價 $1.61,最低 $1.58,最高 $1.75。

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本頁僅供研究參考,不構成投資建議。模型可能出錯。過往表現不代表未來結果。

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